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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Algorithmic construction of SSA-compatible extreme rays of the subadditivity cone and the N = 6 solution

We compute the set of all extreme rays of the 6-party subadditivity cone that are compatible with strong subadditivity. In total, we identify 208 new (genuine 6-party) orbits, 52 of which violate at least one known holographic entropy inequality. For the remaining 156 orbits, which do not violate any such inequalities, we construct holographic graph models for 150 of them. For the final 6 orbits, it remains an open question whether they are holographic. Consistent with the strong form of the conjecture in [1], 148 of these graph models are trees. However, 2 of the graphs contain a “bulk cycle”, leaving open the question of whether equivalent models with tree topology exist, or if these extreme rays are counterexamples to the conjecture. The paper includes a detailed description of the algorithm used for the computation, which is presented in a general framework and can be applied to any situation involving a polyhedral cone defined by a set of linear inequalities and a partial order among them to find extreme rays corresponding to down-sets in this poset.

AdS-CFT correspondence↗
DOE OSTI2018

Sparse Hardware Embedding of Spiking Neuron Systems for Community Detection

We study the applicability of spiking neural networks and neuromorphic hardware for solving general optimization problems without the use of adaptive training or learning algorithms. We leverage the dynamics of Hopfield networks and spin-glass systems to construct a fully connected spiking neural system to generate synchronous spike responses indicative of the underlying community structure in an undirected, unweighted graph. Mapping this fully connected system to current generation neuromorphic hardware is done by embedding sparse tree graphs to generate only the leading-order spiking dynamics. Here, we demonstrate that for a chosen set of benchmark graphs, the spike responses generated on a current generation neuromorphic processor can improve the stability of graph partitions and non-overlapping communities can be identified even with the loss of higher-order spiking behavior if the graphs are sufficiently dense. For sparse graphs, the loss of higher-order spiking behavior improves the stability of certain graph partitions but does not retrieve the known community memberships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Towards an improved understanding of the influence of subpixel vegetation structure on pixel-level spectra: a simulation approach

The planned NASA Hyperspectral Infrared Imager (HyspIRI) mission, equipped with an imaging spectrometer that has the capability of monitoring ecosystems globally, will provide an unprecedented opportunity to address scientific challenges related to ecosystem function and change. However, uncertainty remains around the impact of subpixel vegetation structure, in combination with the point spread function, on pixel-level imaging spectroscopy data. We estimated structural parameters, e.g., leaf area index (LAI), canopy cover, and tree location, from HyspIRI spectral data, with the goal of assessing how subpixel variation in these parameters impact pixel-level imaging spectroscopy data. The fine-scale variability of real vegetation structure makes this a challenging endeavor. Therefore, we utilized a simulation-based approach to counter the time-consuming and often destructive sampling needs of vegetation structural analysis and to simultaneously generate synthetic HyspIRI data pre-launch. Three virtual scenes were constructed, corresponding to the actual vegetation structure in the National Ecological Observatory Network’s (NEON) Pacific Southwest Domain (Fresno, CA). These included an oak savanna, a dense coniferous forest, and a conifer-manzanita-mixed forest. Simulated spectroscopy data for these scenes were then generated using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Simulations first were used to verify the physical model, virtual scene geometrical information, and simulation parameters. This was followed by simulations of HyspIRI data, where within-pixel structural variability was introduced, e.g., by iteratively changing per-pixel canopy cover and tree placement, tree clustering, leaf area index (LAI), etc., between simulation runs for the virtual scenes. Finally, narrow-band vegetation indices (VIs) were extracted from the data in an attempt to describe the variability of the subpixel structural parameters; this was done in order to assess VI robustness to changes in structural “levels”, as well as placement of trees/canopies within the instrument’s instantaneous field-of-view (IFOV). Our ultimate goal is not only to better understand how such subpixel variability influence imaging spectroscopy outputs, but also to better estimate vegetation structural parameters using spectra. We constructed regression models for LAI (R2 = 0.92) and canopy cover (R2 = 0.97) with narrow-band VIs via this simulation approach. Our models ultimately are intended to improve the HyspIRI mission’s ability to monitor global vegetation structure.

Van Aardt, Jan↗
DOE OSTI2021

The Stellar decomposition: A compact representation for simplicial complexes and beyond

Here, we introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex’s vertices and cells such that each region has sufficient information to locally reconstruct the star of its vertices, i.e., the cells incident in the region’s vertices. Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain. They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the complex. As a concrete realization of this model for spatially embedded complexes, we introduce the Stellar tree, which combines a nested spatial tree with a simple tuning parameter to control the number of vertices in a region. Stellar trees exploit the complex’s spatial locality by reordering vertex and cell indices according to the spatial decomposition and by compressing sequential ranges of indices. Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes. We conclude with a high-level description of several mesh processing and analysis applications that utilize Stellar trees to process large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source’s infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model—which make use of different information within a tree—suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dynamic, risk informed decision support systems and methods

The present disclosure is directed to a decision support system or tool based on a Bayesian Network (BN) framework. The diagnostic support tool is created by using advanced Probabilistic Risk Assessment (PRA) method(s) to construct Bayesian Networks (BNs) that form a Bayesian Decision Support Process (BDSP) to provide science-based decision support for understanding and managing events in complex systems. In an embodiment, the PRA method(s) may include Discrete Dynamic Event Trees (DDETs) and simulations.

Groth, Katrina↗
DOE OSTI2015

Attractor comparisons based on density

Recognizing a chaotic attractor can be seen as a problem in pattern recognition. Some feature vector must be extracted from the attractor and used to compare to other attractors. The field of machine learning has many methods for extracting feature vectors, including clustering methods, decision trees, support vector machines, and many others. In this work, feature vectors are created by representing the attractor as a density in phase space and creating polynomials based on this density. Density is useful in itself because it is a one dimensional function of phase space position, but representing an attractor as a density is also a way to reduce the size of a large data set before analyzing it with graph theory methods, which can be computationally intensive. The density computation in this paper is also fast to execute. In this paper, as a demonstration of the usefulness of density, the density is used directly to construct phase space polynomials for comparing attractors. Comparisons between attractors could be useful for tracking changes in an experiment when the underlying equations are too complicated for vector field modeling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

The deconstruction of flavor in the privately democratic Higgs sector

The Standard Model (SM) of particle physics fails to explain the observed hierarchy in fermion masses or the origin of fermion-flavor structure. We construct a model to explain these observations in the quark sector. We introduce a spectrum of new particles consisting of six of each — massive singlet vector-like quarks (VLQs), singlet scalars, and SU(2)-doublet scalars. SM quark masses are generated when the neutral components of the SU(2)-doublet scalars acquire non-zero vacuum expectation values (VEVs). We impose global symmetries to ensure that Yukawa couplings stay roughly flavor diagonal and democratic (of the same order), as well as to suppress tree-level flavor-changing neutral currents. Quark-mass hierarchy then follows from a hierarchy in scalar VEVs. The singlet scalars also acquire weak-scale VEVs. Together with the VLQs, they act as messengers between different generations of quarks in the SM. These messenger particles are responsible for generating the elements of the Cabibbo-Kobayashi-Masakawa (CKM) matrix which depend on the ratios of the singlet VEVs and VLQ masses. Constructed this way, the CKM matrix is found to be independent of the SM fermion masses. Using the measured values of the CKM matrix elements and assuming order-one couplings, we derive constraints on the masses of the VLQs and discuss prospects for probing our model in the near future.

CKM Parameters↗
DOE OSTI2015

Scalable parallel distance field construction for large-scale applications

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Kraken2 Metagenomic Virus Database

The Database: Kraken2 [1] database built from a classification tree containing over 700k metagenomic viruses from JGI IMG/VR [2]. (1) Wood, D. E., Lu, J., and Langmead, B. (2019). Improved metagenomic analysis with Kraken 2. Genome Biol., 20(1), 1–13. doi: 10.1186/s13059-019-1891-0 (2) Paez-Espino D, Chen I-MA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses. Nucleic Acids Res. 2017;45:D457-65. For Paper: Title: A k-mer based approach for virus classification in metatranscriptomic and metagenomic samples identifies viral associations in the Populus phytobiome and autism brains Abstract Background Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an important role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which further limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus' genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples. Methods To identify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses. We then integrated the viral classification tree with the NCBI taxonomy for use with ParaKraken, a metagenomic/transcriptomic classifier. Results To illustrate the breadth of our utility for classifying viruses with ParaKraken, we analyzed data from a plant metagenome study identifying the differences between two Populus genotypes in three different compartments and on a human metatranscriptome study identifying the differences between Autism Spectrum Disorder patients and controls in post mortem brain biopsies. In the Populus study, we identified genotype and compartment specific viral signatures, while in the Autism study we identified a significant increased abundance of eight viral sequences in Autism brain biopsies. Conclusion Viruses represent an important aspect of the microbiome. The ability to classify viruses represents the first step in being able to better understand their role in the microbiome. The viral classification method presented here allows for more complete identification of viral sequences for use in identifying associations between viruses and the host and viruses and other microbiome members. Acknowledgements and Funding This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This research was also supported by the Plant-Microbe Interfaces Scientific Focus Area in the Genomic Science Program, the Office of Biological and Environmental Research (BER) in the U.S. Department of Energy Office of Science, and by the Department of Energy, Laboratory Directed Research and Development funding (ProjectID 8321), at the Oak Ridge National Laboratory. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US DOE under contract DE-AC05-00OR22725. This research used resources of the Compute and Data Environment for Science (CADES).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A Simplified Multi-Path Event Tree for the Integral, Inherently-Safe Light Water Reactor (I{sup 2}S-LWR)

The Integral, Inherently-Safe Light Water Reactor (I{sup 2}S-LWR) concept aims to raise the bar for nuclear power plant safety while maintaining the economic advantages of large, gigawatt-scale plants.1 To obtain this goal, the project safety team seeks to eliminate initiating events where possible, maximize passivity of safety systems, and optimize a balance of redundancy, diversity, and simplicity of safety systems.2 Achievement of these objectives, particularly the last set, requires detailed, quantitative risk information from the earliest stages of development. Therefore, despite limited design information, we have constructed a preliminary probabilistic risk assessment (PRA) for I{sup 2}S-LWR. Safety implementation for I{sup 2}S-LWR, then, requires an iterative process involving system design, thermal-hydraulic (T/H) and neutronic deterministic analyses, and risk-informing PRA studies. Due to this parallelism, it is vital those team members without PRA expertise quickly and correctly understand preliminary PRA results. To this end, we have developed a method to condense the entire PRA into a single, multi-path event tree (MPET). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

A subleading power operator basis for the scalar quark current

Factorization theorems play a crucial role in our understanding of the strong interaction. For collider processes they are typically formulated at leading power and much less is known about power corrections in the λ << 1 expansion. Here we present a complete basis of power suppressed operators for a scalar quark current at O(λ 2 ) in the amplitude level power expansion in the Soft Collinear Effective Theory, demonstrating that helicity selection rules significantly simplify the construction. This basis applies for the production of any color singlet scalar in qq¯¯ annihilation (such as bb¯¯→H ). We also classify all operators which contribute to the cross section at O(λ 2 ) and perform matching calculations to determine their tree level Wilson coefficients. Furthermore, these results can be exploited to study power corrections in both resummed and fixed order perturbation theory, and for analyzing the factorization properties of gauge theory amplitudes and cross sections at subleading power.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2012

Scalla: Structured Cluster Architecture for Low Latency Access

Scalla is a distributed low-latency file access system that incorporates novel techniques that minimize latency and maximize scalability over a large distributed system with a distributed namespace. Scalla's techniques have shown to be effective in nearly a decade of service for the high-energy physics community using commodity hardware and interconnects. We describe the two components used in Scalla that are instrumental in its ability to provide low-latency, fault-tolerant name resolution and load distribution, and enable its use as a high-throughput, low-latency communication layer in the Qserv system, the Large Synoptic Survey Telescope's (LSST's) prototype astronomical query system. Scalla arguably exceeded its three main design objectives: low latency, scaling, and recoverability. In retrospect, these objectives were met using a simple but effective design. Low latency was met by uniformly using linear or constant time algorithms in all high-use paths, avoiding locks whenever possible, and using compact data structures to maximize the memory caching efficiency. Scaling was achieved by architecting the system as a 64-ary tree. Nodes can be added easily and as the number of nodes increases, search performance increases at an exponential rate. Recoverability is inherent in that no permanent state information is maintained and whatever state information is needed it can be quickly constructed or reconstructed in real time. This allows dynamic changes in a cluster of servers with little impact on over-all performance or usability. Today, Scalla is being deployed in environments and for uses that were never conceived in 2001. This speaks well for the systems adaptability but the underlying reason is that the system can meet its three fundamental objectives at the same time.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

A Retrospective Tiered Environmental Assessment of the Mount Storm Wind Energy Facility, West Virginia, USA

Bird and bat fatalities from wind energy projects are an environmental and public concern, with post-construction fatalities sometimes differing from predictions. Siting facilities in this context can be a challenge. In March 2012 the U.S. Fish and Wildlife Service (USFWS) released Land-based Wind Energy Guidelines to assess collision fatalities and other potential impacts to species of concern and their habitats to aid in siting and management. The Guidelines recommend a tiered approach for assessing risk to wildlife, including a preliminary site evaluation that may evaluate alternative sites, a site characterization, field studies to document wildlife and habitat and to predict project impacts, post construction studies to estimate impacts, and other post construction studies. We applied the tiered assessment framework to a case study site, the Mount Storm Wind Energy Facility in Grant County, West Virginia, USA, to demonstrate the use of the USFWS assessment approach, to indicate how the use of a tiered assessment framework might have altered outputs of wildlife assessments previously undertaken for the case study site, and to assess benefits of a tiered ecological assessment framework for siting wind energy facilities. The conclusions of this tiered assessment for birds are similar to those of previous environmental assessments for Mount Storm. This assessment found risk to individual migratory tree-roosting bats that was not emphasized in previous preconstruction assessments. Differences compared to previous environmental assessments are more related to knowledge accrued in the past 10 years rather than to the tiered structure of the Guidelines. Benefits of the tiered assessment framework include good communication among stakeholders, clear decision points, a standard assessment trajectory, narrowing the list of species of concern, improving study protocols, promoting consideration of population-level effects, promoting adaptive management through post-construction assessment and mitigation, and sharing information that can be used in other assessments.

17 WIND ENERGY↗
DOE OSTI2025

The Analysis Description Language Ecosystem: Latest developments and physics applications

We present latest developments in Analysis Description Language (ADL), a declarative domain-specific language describing the physics algorithm of a HEP data analysis decoupled from software frameworks. Analyses written in ADL can be integrated into any framework for various tasks. ADL is a multipurpose construct with uses ranging from analysis design to preservation, reinterpretation, queries, visualisation, combination, etc. The most advanced infrastructure to execute ADL on events is the CutLang runtime interpreter. Recent technical developments include an automated interface with different data types, generation of the abstract syntax tree, a visualization tool that that auto-converts analysis flows to graphs, incorporation of trained machine learning models and a Jupyter-based plotting tool. We also report physics implications including a large scale LHC analysis implementation and validation effort for beyond the standard model reinterpretation purposes and studies with ATLAS and CMS open data.

Sekmen, Sezen [Kyungpook National Univ., Daegu (Ko↗
DOE OSTI2021

The Last Journey. II. SMACC—Subhalo Mass-loss Analysis Using Core Catalogs

Here we introduce Subhalo Mass-loss Analysis using Core Catalogs (SMACC). SMACC adds a mass model to substructure merger trees based on halo "core tracking." Our approach avoids the need for running expensive subhalo finding algorithms and instead uses subhalo mass-loss modeling to assign masses to halo cores. We present details of the SMACC methodology and demonstrate its excellent performance in describing halo substructure and its evolution. Validation of the approach is carried out using cosmological simulations at significantly different resolutions. We apply SMACC to the 1.24-trillion-particle Last Journey simulation and construct core catalogs with the additional mass information. These catalogs can be readily used as input to semianalytic models or subhalo abundance matching approaches to determine approximate galaxy distributions, as well as for in-depth studies of small-scale structure evolution.

79 ASTRONOMY AND ASTROPHYSICS↗